Generally, there are two methods for producing high resolution images. The first method uses a high resolution camera to acquire a high resolution image. The second method uses a low resolution camera to acquire a high resolution image. For example, for using a low resolution web camera to shoot a business card and performing character recognition on the shot image of the business card, an application program is executed to perform an image processing operation on a plurality of low resolution images so as to produce the high resolution image.
A method for producing a high resolution image by using a plurality of low resolution images is disclosed in for example Taiwanese Patent No. TW583603. Hereinafter, the high resolution image producing method according to Taiwanese Patent No. TW583603 will be illustrated with reference to FIG. 1. FIG. 1 is a flowchart illustrating a high resolution image producing method according to the prior art. Firstly, in the step S10, M first images are stored. Then, the step S12 is performed to select one of the M first images as a prototype image, and define the non-selected first images as (M−1) second images. In the step S14, based on the magnification factor, extra pixels are interpolated into the prototype image, and then the two-dimension translation magnitudes existing between respective (M−1) second images and the interpolated prototype image are calculated. Then, in the step S16, the two-dimension translation magnitudes of the (M−1) second images are respectively divided by the magnification factor to obtain the modulus values. Then, one second image is selected from the second images whose related modulus values are the same, and the selected second image together with the rest of the second images whose related modulus values are not the same are defined as N third images. Then, the step S18 is performed to down-sample the interpolated prototype image N according to the respective translation magnitudes between the N third images and the interpolated prototype image, thereby producing N fourth images. In the step S20, the difference between each of the N third images and the corresponding fourth image is calculated. Then, the step S22 is performed to adjust the values of the pixels of the interpolated prototype image according to an average of the difference between each of the N third images and the corresponding fourth image. Then, the step S24 is performed to determine if the values of the pixels of the interpolated prototype image comply with a satisfactory result. If these values do not comply with the satisfactory result, the steps S18 through S22 are repeatedly done until a high resolution image is obtained.
The conventional high resolution image producing method, however, still has some drawbacks. This method comprises three stages to reconstruct the high resolution image: i.e. an initial guessing stage (S10˜S14), an automatic image-selecting stage (S16) and a repeated correcting stage (S18˜S24). Since the repeated correcting stage needs complex and time-consuming computation, the high resolution image or the recognizing result fails to be realized by the user in a short time. In other words, the conventional high resolution image producing method is not user-friendly.